Block 4 Activity 2: Investigating Big Data

For this activity I have to read two online stories about the use of big datasets.

Duhigg (2012) How companies learn your secrets

  • each shopper was assigned a unique code that kept tabs on everything bought
  • demographic information was linked to the code
  • additional data about ethnicity, job history etc was bought to add to the shopper’s profile
  • predictive analytics departments were being created and statisticians were in demand
  • behavioural research was used
  • privacy laws had to be adhered to or else customers would become uncomfortable about how the company knew particular things about them.

Mangalindan (2012) Amazon’s recommendation secrets     Big_data_cartoon_t_gregorius

  • Amazon know more about their customers then Facebook or Google.
  • Use information related to past purchases, items rated/liked and what other customers have also viewed and purchased.
  • ‘item-to-item collaborative filtering’
  • Amazon also use employees to market specific products email offers are filtered to decrease the number of emails sent
  • now using Add-ons for cheaper products – customers are likely to add to their shopping as its only a few pounds more- similar to supermarket special offers

Extending my reading to search for “big data” through google and looking at a larger company – Starbucks.

“Starbucks knows how you like your coffee” Whitten (2016)  Starbucks_Coffee_Logo.svg.png

Reason for using big data:

  • Consumer data was collected to help develop Starbuck’s  new line of products
  • Also used data from several consumer research firms to help with production of new grocery product lines
  • Culled at-home information about consumption of their product.

Who benefited from it’s use?

  • Starbucks and their stakeholders/investors
  • Consumers – got new range of products

What the benefits were:

  • Smart marketing approach allowed Starbucks to move into grocery products
  • Starbucks brand was expanded through creation of K-Cups and bottled beverages and consumption was doubled
  • Using consumer preference gets consumers to avoid other products while shopping/at home.

My reactions to the use of my data

Positives:

  • Can help reduce searches made while shopping or researching
  • Can help develop/produce/improve products to meet my needs

Negatives:

  • encourages over spending when alternatives shown or shared through other people’s buying
  • encourages contact from 3rd parties
  • details can be sold on without consent (small print or box tick missed)
  • Don’t like knowing just how far my details are being used by companies to benefit them
  • It’s not just ‘Big Brother’ watching everything I do online.

References:

Duhigg, C (2012) ‘How companies learn from your secrets’, New York Times Magazine, 16 February, [online] available at http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all&_r=0 (accessed 03 July 2016).

Mangalindon, J. P., (2012) ‘ Amazon’s recommendation secret’, Fortune, 30 July, 11:09 am EDT [online] available at http://fortune.com/2012/07/30/amazons-recommendation-secret/ (accessed 03 July 2016)

Whitten, S. (2016) ‘Starbucks knows how you like your coffee’, CNBC, 6 April, 2.37 pm ET [online] available at http://www.cnbc.com/2016/04/06/ (accessed on 03 July 2016)

Images:

Image by: Thierry Gregorius (Cartoon: Big Data) [CC-BY-2.0 (http://creativecommons.org/licenses/by/2.0)%5D, via Wikimedia Commons

https://en.wikipedia.org/wiki/File:Starbucks_Coffee_Logo.svg

 

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